A hearing impaired person typically suffers from a loss of hearing sensitivity, this loss dependent upon both the frequency and the audible level of the sound in question. Thus a hearing impaired person may be able to hear certain frequencies (e.g., low frequencies) as well as a non-hearing impaired person, but unable to hear sounds with the same sensitivity as the non-hearing impaired person at other frequencies (e.g., high frequencies). Similarly, the hearing impaired person may be able to hear loud sounds as well as the non-hearing impaired person, but unable to hear soft sounds with the same sensitivity as the non-hearing impaired person. Thus, in the latter situation, the hearing impaired person suffers from a loss of dynamic range.
A variety of analog and digital hearing aids have been designed to mitigate the above-identified hearing deficiencies. For example, frequency shaping techniques can be used to contour the amplification provided by the hearing aid, thus matching the frequency dependent hearing losses of the intended user. With respect to dynamic range loss, typically a compressor is used to compress the dynamic range of the input sound so that it more closely matches the dynamic range of the intended user. The ratio of the input dynamic range to the dynamic range output by the compressor is referred to as the compression ratio. Generally the compression ratio required by a user is not constant over the entire input power range.
Typically dynamic range compressors are designed to perform differently in different frequency bands, thus accounting for the frequency dependence (i.e., frequency resolution) of the intended user. Such multi-channel or multi-band compressors divide the input signal into two or more frequency bands, compressing each band separately. This design allows greater flexibility in varying not only the compression ratio, but also the time constants associated with each band. The time constants refer to the attack and release time constants. The attack time is the time required for the compressor to react and lower the gain at the onset of a loud sound. Conversely, the release time is the time required for the compressor to react and increase the gain after the cessation of the loud sound.
Conventional digital signal processing techniques such as those relying upon the discrete Fourier transform (DFT) provide constant bandwidth frequency resolution. Accordingly, such techniques are inappropriate for the present application. FIG. 1 illustrates one prior art approach to overcoming the mismatch between the uniform frequency analysis inherent in conventional digital processing and the non-uniform frequency resolution of the ear. As shown, a multi-channel filter bank 100 is used which is comprised of multiple filters 101 operating in parallel, the filters dividing the input signal 103 into multiple bands. Typically between two and four frequency bands are used in this type of system. The respective filter bandwidths and band edges are chosen to give an approximation to a critical band frequency scale. The compressor independently operates on the output 105 from each filter 101, the compressor output 107 being the sum of the individually compressed signals 109. Although this approach is relatively straightforward to implement and results in only a short digital processing delay, the relatively coarse frequency resolution can limit the ability of the system to provide the desired gain-versus-frequency characteristics commonly required for an arbitrary hearing loss.
FIG. 2 is an illustration of a second prior art approach to overcoming the deficiencies in conventional digital processing as applied to the non-uniform frequency resolution of the ear. In this approach, incoming signal 103 is processed in the frequency domain. A DFT is used for the frequency analysis, typically implemented using a fast Fourier transform (FFT) algorithm. The FFT performed at step 201 must be large enough to provide the desired frequency resolution at low frequencies. Summing overlapping groups of FFT bins forms the high frequency analysis bands. The compression gains are computed in the frequency domain using the power estimates in each analysis band (step 203). The compressor filter is applied in the frequency domain (step 205) and an inverse FFT is used to produce the amplitude-compressed signal (step 207). Operating the system at a 16 kHz sampling rate, a 128-point FFT can be used to process the buffered input data, resulting in 65 frequency samples between 0 and π. From these 65 FFT bins, 14 overlapping frequency bands are formed for use in setting the compression gains. This approach has the advantage of good frequency resolution, but the increased resolution requires a large buffer to hold the input data prior to computing the FFT. As a result of signal buffering, a substantial digital processing delay may be realized, this delay being audible to the user in some situations.
In a modification to the above approach shown in FIG. 3, the compressor uses a side branch 301 for the frequency analysis. The results of the frequency analysis are used to generate the coefficients of a filter 303 placed in the signal path. A filter bank as illustrated in FIG. 1 or an FFT as shown in FIG. 3 is used for the frequency analysis. As with the system shown in FIG. 2, summing overlapping groups of FFT bins at high frequencies provides the approximation to the auditory frequency analysis. The side-branch system illustrated in FIG. 3 results in minimal digital processing delay as the direct signal path contains only the short input buffer 305 and the finite impulse response (FIR) filter 303. The resolution of the frequency analysis performed in the side branch is limited by the size of the FFT and its associated input buffer. In the system illustrated in FIG. 3, again assuming a sampling rate of 16 kHz, a 32-point FFT is computed (step 307) with the positive frequency samples combined to give nine overlapping frequency bands. Increasing the FFT buffer size by including more past samples of the input signal would give better frequency resolution, but would also increase the time lag between changes in the incoming signal amplitude and the modified gain values that are applied to that signal.
Although a variety of different signal processing systems have been implemented in hearing aids, none of the systems have provided the desired frequency resolution in combination with a sufficiently minimal processing time lag. The present invention provides such a system.